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arXiv:2504.01646 · IEEE International Conference on Quantum Computing and Engineering (QCE)

Adaptive Mesh Refinement Quantum Algorithm for Maxwell's Equations

Élise Fressart, Michel Nowak, Nicole Spillane

Published Aug 30, 2025• 0 citations
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Abstract

Algorithms that promise to leverage resources of quantum computers efficiently to accelerate the finite element method have emerged. However, the finite element method is usually incorporated into a high-level numerical scheme which allows the adaptive refinement of the mesh on which the solution is approximated. In this work, we propose to extend adaptive mesh refinement to the quantum formalism, and apply our method to the solution of Maxwell's equations. An important step in this procedure is the computation of error estimators, which guide the refinement. By using block-encoding, we propose a way to compute these estimators with quantum circuits. We present first numerical experiments on a 2D geometry.

DOI
10.1109/qce65121.2025.00043

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Algorithms that promise to leverage resources of quantum computers efficiently to accelerate the finite element method have emerged. However, the finite element method is usually incorporated into a high-level numerical scheme which allows the adaptive refinement of the mesh on which the solution is approximated. In this work, we propose to extend adaptive mesh refinement to the quantum formalism, and apply our method to the solution of Maxwell's equations. An important step in this procedure is the computation of error estimators, which guide the refinement. By using block-encoding, we propose a way to compute these estimators with quantum circuits. We present first numerical experiments on a 2D geometry.
Quantum computing is a rapidly advancing field, driven by the potential advantages derived from the unique properties of quantum entanglement. In particular, the exponential speedup of certain carefully designed algorithms, compared to their classical counterparts, promises to significantly enhance the numerical solution of a wide range of problems. This paper investigates the integration of quantum computing with the finite element method, focusing on singularly perturbed advection-diffusion-reaction problems. We introduce a novel finite element scheme that combines classical and quantum algorithms. In this approach, the primary mesh adaptation loop is managed by a classical computer, while a specific stabilization procedure is executed on a quantum computer. This procedure leverages the Harrow-Hassidim-Lloyd algorithm in conjunction with the swap test to estimate the value of a linear functional, which constitutes a substantial portion of the computational workload. We demonstrate that this hybrid approach effectively eliminates parasitic oscillations in the finite element approximation, even at the early stages of the adaptation process. This leads to a significant improvement in the quality of intermediate finite element solutions. As a result, our scheme offers more efficient feedback with reduced computational costs for researchers using the method to investigate physical phenomena. To support the scheme, we prove special explicit a posteriori error estimates. Possible benefits of the proposed finite element scheme are analyzed using the numerical comparison with the typical adaptive scheme.
The finite element method (FEM) is a cornerstone numerical technique for solving partial differential equations (PDEs). Here, we present Qu-FEM\textbf{Qu-FEM}Qu-FEM, a fault-tolerant era quantum algorithm for the finite element method. In contrast to other quantum PDE solvers, Qu-FEM preserves the geometric flexibility of FEM by introducing two new primitives, the unit of interaction and the local-to-global indicator matrix, which enable the assembly of global finite element arrays with a constant-size linear combination of unitaries. We study the modified Poisson equation as an elliptic problem of interest, and provide explicit circuits for Qu-FEM in Cartesian domains. For problems with constant coefficients, our algorithm admits block-encodings of global arrays that require only O~(d2p2n)\tilde{\mathcal{O}}\left(d^2 p^2 n\right)O~(d2p2n) Clifford+TTT gates for ddd-dimensional, order-ppp tensor product elements on grids with 2n2^n2n degrees of freedom in each dimension, where nnn is the number of qubits representing the N=2nN=2^nN=2n discrete grid points. For problems with spatially varying coefficients, we perform numerical integration directly on the quantum computer to assemble global arrays and force vectors. Dirichlet boundary conditions are enforced via the method of Lagrange multipliers, eliminating the need to modify the block-encodings that emerge from the assembly procedure. This work presents a framework for extending the geometric flexibility of quantum PDE solvers while preserving the possibility of a quantum advantage.
This paper presents a novel quantum simulation framework designed to address challenges in fluid dynamics simulation, specifically focusing on achieving high accuracy and efficiency. The core innovation lies in the implementation of an Adaptive Mesh Refinement (AMR) technique, which dynamically adjusts the mesh density based on the complexity of the flow field. This mechanism ensures optimal computational resources are utilized, leading to improved simulation performance compared to traditional, static mesh approaches. The theoretical foundations of the proposed method are established through a rigorous analysis of the flow dynamics involved. The paper details the architecture of the simulation, the implementation of the AMR algorithm, and the validation of the framework using a series of challenging fluid dynamics problems. The results demonstrate a significant improvement in accuracy and computational efficiency compared to existing methods, highlighting the potential of this approach for advanced fluid dynamics modeling.
Quantum simulation of electromagnetic (EM) structures is still in its infancy. In this paper, we investigate the possibility of applying quantum computing to solve the finite element equations for EM problems. Specifically, we propose to leverage a milestone in quantum computing, i.e., the Harrow/Hassidim/Lloyd (HHL) algorithm, to solve the finite element equations in the EM domain. To do this, we first present a systematic method to reformulate the finite element equations into quantum computation format and apply the HHL algorithm to solve the new equations. Taking advantage of the special properties of finite element matrices in EM problems, we then devise a stepwise algorithm to efficiently determine the suitable values for the hyperparameters of HHL. The proposed method can in theory solve the EM finite element equations in logarithmic time relative to the size of the finite element matrix. This is exponentially faster than that achievable by classical computation as the matrix size increases. A two-dimensional EM example is used to illustrate how the proposed method can be used to find the solutions to EM problems through quantum computation.
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Quantum computing is a potential approach for addressing computational challenges in solving electromagnetic problems. A quantum method, called the Harrow/Hassidim /Lloyd (HHL) algorithm has recently been applied to solve the equations from finite-element-method (FEM) formulation of electromagnetic problems. Here we address a further step in this direction. Since quantum state vectors always have unit norm, the solution vector from HHL is only proportional to the final electromagnetic solutions. The magnitude of the final electromagnetic solution vector remains unavailable from HHL In this paper, a new quantum formulation is proposed to find the magnitude of the final electromagnetic solutions. The proposed method can be used to scale the HHL results to the correct magnitude of electromagnetic solutions. In this way, the proposed method is a further advance in making the quantum computing more effective in solving electromagnetic problems.